Search Results - EGA European Genome-Phenome Archive

SF11612 scRNA-Seq Recurrent oligodendroglioma

Single Cell RNA seq from Recurrent oligodendroglioma sample. Gender Male Age 67. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference through Cellranger count (10xGenomics.)

Dataset EGAD00001005411

SF12090 snRNA-Seq IDHR132H Wild-type Primary GBM Male

Single Nuclei RNA-Seq Primary IDHR132H Wild-type GBM. Male, 61. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005412

SF11612 snATAC Seq Recurrent oligodendroglioma

SF11612 Recurrent oligodendroglioma. Gender Male Age 67. Single Nuclei ATAC seq data from low grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005413

SF11964 snATAC Seq Low Grade Astrocytoma IDHR132H mutant

Single Nuclei ATAC Seq IDHR132H mutant Astrocytoma . Male, 64. Single Nuclei ATAC seq data from low grade human glioma sample. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005414

SF4297 snRNA-Seq Primary GBM

Single Nuclei RNA-Seq Primary High-grade Glioma. Gender male age 39. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference

Dataset EGAD00001005415

SF11979 snATAC seq IDHR132H Wildtype GBM Female

SF11979 snATAC, IDHR132H WT GBM Female, 76 Single Nuclei ATAC seq data from high grade human glioma samples. NovaSeq6000 was used for ATAC seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005418

CyTOF of 27 DLBCLs

Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin lymphoma and is notorious for its clinical heterogeneity. Patient outcomes can be predicted by cell-of-origin (COO) classification, demonstrating that the underlying transcriptional signature of malignant B-cells informs biological behavior in the context of standard combination chemotherapy regimens. In the current study, we used mass cytometry (CyTOF) to examine tumor phenotypes at the protein level with single cell resolution in a collection of 27 diagnostic DLBCL biopsy specimens from treatment naïve patients. We found that malignant B-cells from each patient occupied unique regions in 37-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Interestingly, variable MHC class II expression was found to be the greatest contributor to phenotypic diversity. Within individual tumors, a subset of cases showed multiple phenotypic subpopulations, and in one case we were able to demonstrate direct correspondence between protein-level phenotypic subsets and DNA mutation-defined subclones. In summary, CyTOF analysis can resolve both inter- and intra-tumoral heterogeneity among primary samples, and reveals that each case of DLBCL is unique and may be comprised of multiple, genetically distinct subclones.

Dataset EGAD00001005419

SF9259S snRNA-Seq Primary GBM

Single Nuceli Primary GBM 73 Male. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005428

SF11979 scRNA-Seq Primary GBM IDHR132H Wild-type Female

Single Cell Prmary high grade glioma IDHR132H Wild-type Female 76 Single Cell RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005429

SF11979 snRNA-Seq Primary GBM IDHR132H Wildtype Female

Single Nuclei Primary GBM IDHR132H Wildtype. Female 76. Single Nuclei RNA seq from high grade primary glioma sample. NovaSeq6000 was used for RNA seq. The files uploaded are bam files created with grch38 reference.

Dataset EGAD00001005430

Dataset of whole-exome sequencing of intravascular large B-cell lymphoma

This dataset includes 44 bam files derived of 21 patients with IVL. Tumor samples are derived from cfDNA (n = 18), PDX (n = 4) and bone marrow (n = 2). Normal samples are derived from peripheral blood.

Dataset EGAD00001005445

WXS files for Zhang PanNBL

WXS files for Zhang PanNBL paper titled "Pan-neuroblastoma analysis reveals age- and signature-associated driver alterations"

Dataset EGAD00001005484

preinvasive LUAD

Whole-exome sequencing coupled with RNA-seq of preinvasive (n=98) and invasive (n=99) lung adenocarcinoma samples.

Dataset EGAD00001005479

Myeloma XI trial data

The dataset contains WGS and RNA-seq from Myeloma XI trial

Dataset EGAD00001005491

Reconstruction of complex rearrangement patterns causing the initiation of clear cell renal cell carcinoma.

The genomic hallmark of clear cell renal cell carcinoma is the loss of the short arm of chromosome three. This appears to be the earliest genomic event in the formation of these cancers. Often chromosome 3 is lost at the same time as part of chromosome 5 is duplicated via an unbalanced translocation, often with features consistent with focal chromothripsis. In this study, we sought to reconstruct the chromothriptic event that underlies the initiation of kidney cancer. We used long read sequencing (promethION, Oxford Nanopore Technologies) of patient tumour-derived DNA to elucidate how a single cell division error can generate cancer genome complexity.

Dataset EGAD00001005495

HIPO016 - glioblastoma tumour methylation microarray profiling

Methylation microarray profiling (Illumina Human Methylation 450k and EPIC platforms) of 60 adult glioblastomas. Tumours were subtyped using the approach from Sturm et al. (https://doi.org/10.1016/j.ccr.2012.08.024): 12 IDH, 18 MES, 12 RTK I, 18 RTK II. DNA was prepared, assayed on the microarrays, and raw data computationally processed as described in Capper et al., "DNA methylation-based classification of central nervous system tumours": https://www.nature.com/articles/nature26000

Dataset EGAD00010001797

Cell type-specific transcriptomics of esophageal adenocarcinoma

3' mRNA-Seq obtained from distinct isolated cell types (epithelia cells,immune cells, fibroblasts) of endoscopically obtained esophageal adenocarcinoma tissue as well as normal esophageal mucosa. Libraries for RNA-sequencing were prepared using the QuantSeq 3' mRNA-Seq Library Prep Kit FWD for Illumina according to the low input protocol. Libraries were sequenced on a HiSeq 4000 (Illumina) by 1x 50 bases.

Dataset EGAD00001005508

UCSF Pediatric Bithalamic Glioma Genome Project

Targeted next-generation sequencing of 13 pediatric bithalamic diffuse gliomas. BAM files of targeted next-generation DNA sequencing data of 13 pediatric gliomas, with multi-region sequencing data from 2 of these cases (17 total tumor samples). Genomic DNA was extracted from formalin-fixed, paraffin-embedded blocks of tumor tissue from using the QIAamp DNA FFPE Tissue Kit (Qiagen). Capture-based next-generation DNA sequencing was performed at the University of California, San Francisco Clinical Cancer Genomics Laboratory, using an assay that targets all coding exons of 480 cancer-related genes, select introns of 47 genes, and TERT promoter with a total sequencing footprint of 2.8 Mb (UCSF500 Cancer Panel). Sequencing libraries were prepared from genomic DNA, and target enrichment was performed by hybrid capture using a custom oligonucleotide library (Nimblegen SeqCap EZ Choice). Captured libraries were sequenced as paired-end 100 bp reads on an Illumina HiSeq 2500 instrument. Duplicate sequencing reads were removed computationally to allow for accurate allele frequency determination and copy number calling.

Dataset EGAD00001005499

20191008_EGA_MELA_Acral_WGS+RNASeq

Illumina platform sequencing of whole genome libraries prepared from paired tumour/normal samples from 87 cases of melanoma Acral subtype. 63 cases also have RNASeq sequencing from the tumour sample.

Dataset EGAD00001005500

20191008_EGA_MELA_Immunology

Illumina RNASeq sequencing of tumour samples from 41 cases of melanoma

Dataset EGAD00001005501

ICGC_Pedbrain_WGBS_Pilocytic_Astrocytoma

18 WGBS lanes for 9 samples of pilocytic astrocytoma.

Dataset EGAD00001005504

Sequencing files for "A Unifying Paradigm for Transcriptional Heterogeneity and Squamous Features in Pancreatic Ductal Adenocarcinoma."

Files from DNA and RNA sequencing from primary tumors and metastases from pancreatic cancer patients along with matched normal tissues.

Dataset EGAD00001005519

A Protein Neddylation Inhibitor MLN4924 Suppresses Patient-Derived Glioblastoma Cells via Inhibition of ERK and AKT Signaling

To identify what factors cause a different reactivity to MLN4924, 15 cells were categorized into high, intermediate, and low MLN4924 resistance groups based on the half-maximal inhibitory concentration (IC50) of MLN4924. PDC1, PCD2, PDC3, PDC4, and PDC5 showed high MLN4924 sensitivity, whereas PDC12, PDC13, PDC14, and PDC15 showed low MLN4924 sensitivity. Whole-transcriptome sequencing of these 9 patient-derived glioblastoma stem cells was performed.

Dataset EGAD00001005709

Uncovering tumor intrinsic and extrinsic factors that regulate hepatocellular carcinoma growth using patient derived xenograft assays

Exome Sequencing and RNA Sequencing Data for PDX Samples

Dataset EGAD00001005734

20191204_EGA_MELA_Rizos

79 RNAseq samples from 56 patients with melanoma who have undergone immune checkpoint blockade immunotherapy.

Dataset EGAD00001005738

Single-cell expression of Hodgkin lymphoma

Single-cell gene expression was profiled for 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes (2 replicates were performed for RLN-1). Library preparation was performed with the 10x Chromium platform (3' version 2 assay). Sequencing was performed on an Illumina NextSeq. The BAM files were generated from the raw sequencing data using Cell Ranger (v2.1.0) mkfastq and count commands.

Dataset EGAD00001005739

KRAS Mutations in Multiple Myeloma

Fastq files for 80 Multiple Myeloma Patients and 12 cell-lines

Dataset EGAD00001005743

Whole genome sequencing generated from metastatic gliosarcoma patient samples

This dataset contains whole genome sequencing data aligned to the b37 reference genome for 4 spatially and temporally distinct tumors from one patient with a matched normal blood sample.

Dataset EGAD00001005745

Somatic mutation and clonal evolution in the human pancreas - WGS (2019-12-17)

In this study we aim to characterise the landscape of mutation and clonal selection in the human pancreas. The study combines targeted sequencing and whole-genome sequencing of microbiopsies from the pancreas. The range of patients studied will include healthy individuals, both smokers and non-smokers, and patients with pancreatic ductal adenocarcinoma. This dataset contains all the data available for this study on 2019-12-17.

Dataset EGAD00001005751

Phased melanoma whole genomes

We have sequenced whole genomes of 10 melanoma samples (1 cell line; A375 and 9 patient derived short term cultures). Libraries were prepared with 10X linked reads technology in order to obtain phase information and subsequently sequenced on Illumina NovaSeq6000.

Dataset EGAD00001005773

Targeted Sequencing of Tumor-Normal pairs from advanced Melanoma

Aligned BAM files from NextSeq500 tageted panel sequencing of 84 samples from matched tumour-normal pairs of 42 melanoma patients. The dataset consists of 30 non-responders and 12 responders to ICB.

Dataset EGAD00001005778

Chromatin run-on and transcriptome sequencing of fibrolamellar carcinoma

Fastq files of chromatin run-on (14 fibrolamellar carcinoma, 3 non-malignant liver; single-end) and transcriptome (23 fibrolamellar carcinoma, 2 non-malignant liver; paired-end) sequencing of fibrolamellar carcinoma

Dataset EGAD00001005797

JAK and STAT alterations in CD30 positive LPD

JAK and STAT alterations in CD30 positive LPD, panel sequencing, 12 cutaneous lymphoma patients, 40 samples

Dataset EGAD00001005801

sWGS of RCC patients

Paired end shallow whole genome sequencing (sWGS) data for the identification of somatic copy number alterations (SCNA) and the estimation of tumor fractions in plasma DNA of renal cell carcinoma (RCC) patients (MonRec Cohort)

Dataset EGAD00001005804

Mutation analysis of 10 genes in plasma DNA of RCC patients

Mutation analysis of 10 frequently mutated genes in renal cell carcinoma (BAP1, KDM5C, MET, MTOR, PBRM1, PIK3CA, PTEN, SETD2, TP53, VHL) in plasma DNA of RCC patients using a custom QIASeq panel (MonRec Cohort)

Dataset EGAD00001005806

Spatial whole exome sequencing of metastatic melanoma

We performed whole exome sequencing of 8 samples derived from a patient with metastatic melanoma. These represent six different regions of a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor, one pre-treatment biopsy that was treatment naive and one post-PD-1 inhibitor treated lesion. Exome sequencing data was generated using methods as previously described, including library preparation using the Agilent SureSelect XT Target Enrichment protocol (#5190-8646) prior to sequencing on an Illumina HiSeq 2000/2500 v3 system using 76bp paired-end reads. Raw sequencing data was then processed using Saturn V, the next generation sequencing data processing and analysis pipeline developed by the Department of Genomic Medicine at the UT MD Anderson Cancer Center.

Dataset EGAD00001005819

Spatial RNA-sequencing of metastatic melanoma

We performed RNA sequencing of 48 different regions sub-sampled from a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. RNAseq was performed on samples with a minimum RNA integrity number (RIN) of 5.5 except for two cases (6A10 and 8A3) with RINs greater than 3. A minimum of 700ng of RNA were required for all samples undergoing RNAseq. Paired-end transcriptome reads were aligned using TopHat2, to the UCSC hg19 reference genome.

Dataset EGAD00001005820

Spatial targeted gene sequencing of metastatic melanoma

We performed deep targeted DNA sequencing for a panel of 265 cancer-related genes. This included subsampling 35 different regions of a metastatic melanoma biopsy that was treated with anti-PD-1 inhibitor. Samples with cancer cell purity greater than 80% based on pathologic assessment were used for cancer gene panel DNA sequencing. Mean sequencing coverage was 861x and paired-end reads in FASTQ format were generated by the Illumina pipeline and aligned to the reference human genome hg19 build using the Burrows-Wheeler Alignment Tool (BWA, v0.7.5) with default settings. Aligned reads were further processed using GATK with best practices for removing duplicates, indel removal and recalibration.

Dataset EGAD00001005821

Genome and transcriptome sequence data from a breast ductal carcinoma patient

Genome and transcriptome sequence data from a breast ductal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

Dataset EGAD00001005823

mtDNA-Roma

mtDNA variant positions vcf files for 86 human samples

Dataset EGAD00010001844

Genome and transcriptome sequence data from an uveal melanoma patient

Genome and transcriptome sequence data from an uveal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

Dataset EGAD00001005824

Genome and transcriptome sequence data from a metastatic rectal carcinoma patient

Genome and transcriptome sequence data from a metastatic rectal carcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

Dataset EGAD00001005825

Genome and transcriptome sequence data from a metastatic choroidal melanoma patient

Genome and transcriptome sequence data from a metastatic choroidal melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

Dataset EGAD00001005828

Genome and transcriptome sequence data from a poorly differentiated adenocarcinoma more consistent with metastatic melanoma patient

Genome and transcriptome sequence data from a poorly differentiated adenocarcinoma more consistent with metastatic melanoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

Dataset EGAD00001005831

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